Search Results - (( problem application usage algorithm ) OR ( using optimization based algorithm ))

Optimal Placement of Phasor Measurement Unit (PMU) using genetic algorithm & cuckoo search algorithm by Midi, Nur Shahida, Mohd Hanfi, Nurhazwani, Hussin, Mohd Fahmi, Abu Hanifah, Mohd Shahrin

“…This work investigates the use of metaheuristic algorithms to solve the Optimal PMU Placement (OPP) problem, aiming to minimize the number of PMUs required. …”
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An analysis of the parameter modifications in varieties of harmony search algorithm by Mansor, N. F., Abal Abas, Zuraida, Abdul Rahman, Ahmad Fadzli Nizam, Shibghatullah, Abdul Samad, Safiah , Sidek

“…A Harmony Search (HS) algorithm is a population based-meta-heuristics approach that is superior in solving diversified and large scale optimization problems. …”
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Battery energy storage system sizing using PSO algorithm in DIgSILENT powerfactory by Gan, Chin Kim, Tan, Pi Hua, Al-Areqi, Khaldon Ahmed Qaid, Tee, Wei Hown

“…The IEEE 9-bus system is the test case used to demonstrate and discuss the application of algorithms in DPL script. …”
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GENETIC ALGORITHM WITH DEEP NEURAL NETWORK SURROGATE FOR THE OPTIMIZATION OF ELECTROMAGNETIC STRUCTURE by MOHAMMED SHARIFF, NUR ATIQAH

“…This paper will report on an initial study of the usage of Genetic Algorithm (GA) merged with Deep Neural Network based surrogate model to optimize simulation for electromagnetic structure. …”
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Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

“…These algorithms can be used successfully in many applications requiring the optimization of a certain multi-dimensional function. …”
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Assisted History Matching by Using Genetic Algorithm and Discrete Cosine Transform by Abdul Rashid, Abdul Hadi

“…Later, an algorithm combining both Genetic Algorithm and Discrete Cosine Transform was proposed, which shows the step-by-step sequence of both methods. …”
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Resource-Efficient Coverage Path Planning for UAV-Based Aerial IoT Gateway by Nurul Saliha A. Ibrahim, Nurul Saliha A. Ibrahim, Faiz A. Saparudin, Faiz A. Saparudin

“…As a result, the Energy Efficient Coverage Path Planning (EECPP) algorithm has been proposed. The EECPP is composed of two algorithms: the Stop Point Prediction Algorithm using K-Means, and Path Planning Algorithm using Particle Swarm Optimization. …”
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Applying case reuse and Rule-Based Reasoning (RBR) in object-oriented application framework documentation: Analysis and design by Jani H.M., Lee S.P.

“…The use of rule-based reasoning and genetic algorithms will optimize the case search and case adaptation process. �2008 IEEE.…”

Evaluation and optimization of frequent association rule based classification by Izwan Nizal Mohd Shaharanee, Jastini Jamil

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Application of system identification method coupled with evolutionary algorithms for the optimization of power consumption in a pem fuel cell propulsion system / Suhadiyana Hanapi by Hanapi, Suhadiyana

“…This thesis makes a number of key contributions to the advancement of fuel cell vehicle design within two main research areas; powertrain system design based on quality energy, and optimization system based on biology based algorithms. …”
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Optimization ofhybrid flow shop scheduling in a machine shop: Achieving energy efficiency and minimizing machine idleness with multi-objective Tiki Taka optimization by Siti Nurhazwani Husna, Mohd Hata, Muhammad Ammar, Nik Mu’tasim, Mohd Fadzil Faisae, Ab Rashid

“…The EE-HFS was optimized using Multi-Objective Tiki Taka Optimization (MOTTA).The study considered machine idle time as a key factor influencing energy efficiency, incorporating it into the scheduling evaluation.The optimization result was compared to established algorithms, such as the Non-dominated Sorting Genetic Algorithm-II, the Multi-ObjectiveEvolutionary Algorithm Based on Decomposition, the Multi-ObjectiveParticle Swarm Optimization,and the recent algorithm,the Multi-ObjectiveGrey Wolf Optimizer. …”
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Optimization of hybrid flow shop scheduling in a machine shop: Achieving energy efficiency and minimizing machine idleness with multi-objective Tiki Taka optimization by Siti Nurhazwani Husna, Mohd Hata, Muhammad Ammar, Nik Mu’tasim, Mohd Fadzil Faisae, Ab Rashid

“…The study considered machine idle time as a key factor influencing energy efficiency, incorporating it into the scheduling evaluation. The optimization result was compared to established algorithms, such as the Non-dominated Sorting Genetic Algorithm-II, the Multi Objectives Evolutionary Algorithm Based on Decomposition, the Multi Objectives Particle Swarm Optimization, and the recent algorithm Multi Objectives Grey Wolf Optimizer. …”
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A strategy for reliability-based multidisciplinary design optimization of wind turbine using BLISS and PMA by Mousavi, S. A., Romli, Fairuz Izzudin

“…However, the major challenges of UMDO, namely computational complexity and organizational complexity caused by both time-consuming disciplinary analysis models and UMDO algorithms, still greatly hamper its usage in wind engineering. …”
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Energy management system for optimal operation of microgrid consisting of PV, fuel cell and battery / Shivashankar Sukumar by Shivashankar , Sukumar

“…The BESS sizing problem is solved using grey wolf optimizer (GWO), particle swarm optimization (PSO), artificial bee colony (ABC), gravitational search algorithm (GSA), and genetic algorithm (GA). …”
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Modelling of assembly line balancing with energy consumption by Ariff Nijay, Ramli, Mohd Fadzil Faisae, Ab Rashid

“…The Particle Swarm Optimization (PSO) algorithm was applied and the model was tested by using three problems which consist of each of a small, medium, and large-sized test problem. …”
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Dynamic user preference parameters selection and energy consumption optimization for smart homes using deep extreme learning machine and bat algorithm by Shah, Abdul Salam, Mohamad Nasir, Haidawati, Fayaz, Muhammad, Lajis, Adidah, Ullah, Israr, Shah, Asadullah

“…We applied a deep extreme learning machine approach to predict the user parameters. We have used the Bat algorithm and fuzzy logic to optimize energy consumption and comfort index management. …”
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Evaluation and optimization of frequent, closed and maximal association rule based classification by Mohd Shaharanee, Izwan Nizal, Hadzic, Fedja

“…Real world applications of association rule mining have well-known problems of discovering a large number of rules, many of which are not interesting or useful for the application at hand.The algorithms for closed and maximal item sets mining significantly reduce the volume of rules discovered and complexity associated with the task, but the implications of their use and important differences with respect to the generalization power, precision and recall when used in the classification problem have not been examined.In this paper, we present a systematic evaluation of the association rules discovered from frequent, closed and maximal item set mining algorithms, combining common data mining and statistical interestingness measures, and outline an appropriate sequence of usage.The experiments are performed using a number of real-world datasets that represent diverse characteristics of data/items, and detailed evaluation of rule sets is provided as a whole and w.r.t individual classes. …”
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Short Text Classification Using An Enhanced Term Weighting Scheme And Filter-Wrapper Feature Selection by Alsmadi, Issa Mohammad Ibrahim

“…In the second stage, grey wolf optimization (GWO) algorithm, a new heuristic search algorithm, uses the SVM accuracy as a fitness function to find the optimal subset feature.…”
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Bayesian Framework based Brain Source Localization Using High SNR EEG Data by Jatoi, M.A., Kamel, N., Gaho, A.A., Dharejo, F.A.

“…These sources can be localized using different optimization algorithms. This localization information is usable for diagnoses of brain disorders such as epilepsy, Schizophrenia, depression and Alzheimer. …”
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Energy-aware task scheduling for streaming applications on NoC-based MPSoCs by Abd Ishak, Suhaimi Abd Ishak, Wu, Hui, Tariq, Umair Ullah

“…We propose a novel unified approach that integrates task-level software pipelining with Dynamic Voltage and Frequency Scaling (DVFS) to solve the problem. Our approach is supported by a set of novel techniques, which include constructing an initial schedule based on a list scheduling where the priority of each task is its approximate successor-tree-consistent deadline such that the workload across all the processors is balanced, a retiming heuristic to transform intraperiod dependencies into inter-period dependencies for enhancing parallelism, assigning an optimal discrete frequency for each task and each message using a Non-Linear Programming (NLP)-based algorithm and an Integer-Linear Programming (ILP)-based algorithm, and an incremental approach to reduce the memory usage of the retimed schedule in case of memory size violations. …”
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